Red Hat Data Grid

Video Thumbnail
Video

Cross datacenter replication and disaster recovery with Red Hat JBoss Data Grid

Red Hat Developer Program

Watch this demo to see how Red Hat JBoss Data Grid provides fast, in-memory access to data and elastic scale to your application. Learn how you can achieve fault tolerance and resiliency when multiple copies of data are distributed across the grid and automatically backed up to other datacenters. JBoss Data Grid allows you to scale, boost application performance, and quickly recover from a disaster scenario.

Video Thumbnail
Video

JavaOne 2012: The JBoss Data Grid, or Enterprise-grade Infinispan

Red Hat Developer Program

In an increasing number of disciplines and industries, data volume and complexity has become both a challenge and an opportunity. Application developers are tasked with bridging the gap between challenge and opportunity and one tool in a developer's belt to help build that bridge is a data grid. Red Hat JBoss Data Grid - the supportable version of the Infinispan open source project - is a manageable, scalable, highly available, distributed, in-memory data store that lets you scale horizontally, based on memory and distribution across commodity hardware rather than relational database management system (RDBMS) licenses, database expertise or specialist hardware. Manik Surtani will provide a high-level overview of Red Hat JBoss Data Grid, discussing its benefits, common use-cases, and specific features meant to address today's data challenges and opportunities. Presenter: Manik Surtani Bio: Manik Surtani is a core R&D engineer at Red Hat JBoss Middleware. He is the founder of the Infinispan project, which he currently leads. He is also the spec lead of JSR 347 (Data Grids for the Java Platform), and represents Red Hat on the Expert Group of JSR 107 (Temporary caching for Java). His interests lie in cloud and distributed computing, big data and NoSQL, autonomous systems and highly available computing. He has a background in artificial intelligence and neural networks, highly available e-commerce systems and enterprise Java. Surtani is a strong proponent of open source development methodologies, ethos, and collaborative processes, and has been involved in open source since his first forays into computing.

Video Thumbnail
Video

JavaOne 2012: No sweat with JBoss Data Grid

Red Hat Developer Program

Scale, elasticity, flexibility, low latencies, fault tolerance. These are all things we expect from our modern cloud, Platform-as-a-Service (PaaS), and web application deployments. Tristan and Shane will discuss why these characteristics are crucial to high-performing deployments and show how data grids are the perfect solution to these uniquely big data challenges. Presenter: Shane Johnson Bio: Shane Johnson is responsible for technical marketing strategy and content delivery for Red Hat JBoss Enterprise Application Platform and Red Hat JBoss Data Grid. Previously, he served as a Java EE architect and subject matter expert for Red Hat JBoss Data Grid, working with enterprise customers in the financial and telecommunications industries to integrate data grids into their solutions. His interest in NoSQL began when he published his first NoSQL blog post in the fall of 2009 and has grown ever since.

Video Thumbnail
Video

JavaOne 2012: JPA vs NoSQL: face the conflict with Hibernate OGM

Red Hat Developer Program

Hibernate OGM explores how to map the Java Persistence APIs with various underlying NoSQL stores. While NoSQL datastores offer interesting benefits in the BigData world we enter, choosing the right one for your project can be challenging. Abstracting behind JPA relieves you from the programming API/model shift. But is it possible? In this presentation, we will give an brief overview of the NoSQL landscape, describe how Hibernate OGM persists data in key/value stores, document stores, column family stores, etc. and see where using such an abstraction makes sense in applications. After this presentation, you will have a clearer view on how to integrate NoSQL datastores in your Java projects at least via JPA. Presenter: Emmanuel Bernard Bio: Emmanuel Bernard is data platform architect at Red Hat JBoss Middleware and member of the Hibernate team. After graduating from Supelec (French "Grande Ecole"), Emmanuel has spent a few years in the retail industry as developer and architect where he started to be involved in the ORM space. He joined the Hibernate team in 2003. Emmanuel has lead the JPA implementation of Hibernate. He has founded and leads Hibernate Search, Hibernate Validator and the newcomer Hibernate OGM. Emmanuel is a member of the JPA 2.1 expert group and the spec lead of Bean Validation. He is a regular speaker at various conferences and JUGs, including JavaOne, JBoss World and Devoxx and the co-author of [Hibernate Search in Action](/books/hsia/) published by Manning. He is also founder and co-host of two podcasts: [JBoss Community Asylum](http://asylum.jboss.org) and [Les Cast Codeurs Podcast](http://lescastcodeurs.com). You can follow him on twitter at @emmanuelbernard http://twitter.com/emmanuelbernard.

Video Thumbnail
Video

Scaling In-Memory Data Grid Automatically With Kubernetes (Ray Tsang)

Red Hat Developer Program

Kubernetes is a powerful, open source, container orchestration and cluster management tool from Google. It drew upon all the lessons learned from a near-decade of using containers at Google. In this session, we'll look beyond container orchestration with Kubernetes and take a deep dive into more advanced features such as autoscaling. But its most powerful feature is its versatile REST API, which you can use to tailor Kubernetes to your needs. In addition to the out-of-the-box Kubernetes Autoscaler, we'll look at: - How to access the Kubernetes API securely - The different Kubernetes resources such as Pod, Replication Controller, Service, etc. - How to update/manage your entire cluster using the API We'll use the techniques and the REST API to demonstrate how to cluster Infinispan, an in-memory data grid, in Kubernetes, and autoscale Infinispan using custom metrics.

Video Thumbnail
Video

Full Stack Development With Node.Js And NoSQL (Nic Raboy & Arun Gupta)

Red Hat Developer Program

In this session, we'll talk about what's different about this generation of web applications and how a solid development approach must consider the latency, throughput, and interactivity demand by users across mobile devices, web browsers, and Internet of Things (IoT). We'll demonstrate how to include Couchbase in such applications to support a flexible data model and the easy scalability required for modern development. We'ill demonstrate how to create a full stack application focusing on the CEAN stack, which is composed of Couchbase, Express Framework, AngularJS, and Node.js.

Video Thumbnail
Video

Building Reactive Applications With Node.Js Data Grid (Galder Zamarreño & Divya Mehra)

Red Hat Developer Program

Node.js is a very popular framework for developing asynchronous, event-driven, reactive applications. Red Hat JBoss Data Grid, an in-memory distributed database designed for fast access to large volumes of data and scalability, has recently gained compatibility with Node.js letting reactive applications use it as a persistence layer. Thanks to near caching, JBoss Data Grid offers excellent response times for data queried regularly, and its continuous remote event support means data can get pushed from the data grid to the Node.js application instead of having to wait for the data grid to serve it. In this session, we'll show how to build Node.js applications that use JBoss Data Grid as a persistence layer.

Log aggreator using Fuse and Data Grid
Article

Implementing a Log Collector using Red Hat JBoss Fuse and Red Hat JBoss Data Grid

Hugo Guerrero

Most of the time, when we think about collecting, parsing and storing Logs, the first thing that pops in our mind is the ElasticStack or ELK. It is well positioned in developer and sysadmin's minds. The stack combines the popular Elasticsearch, Logstash and Kibana projects together to easy the collection/aggregation, store, and visualization of application logs. As an Apache Camel rider and Infinispan enthusiast, I prepared this exercise to produce my own log collector and store stack using Red Hat's...

Red Hat JBOSS Data Grid
Article

Using JBoss DataGrid in Openshift PaaS

Francesco Marchioni

This article describes how to run a client-server application for JBoss Data Grid on Openshift using Red Hat Container Development Kit 3.0 Beta and Minishift. This environment for this tutorial can be set up quickly following up this previous post on the Developer Blog. First of all, you need to make sure you have available the ImageStreams and Templates, in order to run JBoss Data Grid in your Openshift Paas. You can check that your environment contains both of them...

Red Hat JBOSS Data Grid
Article

What’s new in Red Hat JBoss Data Grid 7.1

Cojan van Ballegooijen

We're excited to announce the availability of Red Hat JBoss Data Grid (JDG) Version 7.1. Thanks and congratulations to the JDG engineering and product management team for this release. JDG 7.1 release focuses on the following areas: Performance enhancements Apache Spark 2.x integration Several other enhancements The following new features were added in support of these themes: Release Highlights Performance enhancements JDG 7.1 features core performance improvements, especially in clustered write operations. Current tests have shown up to 60% increase...

Red Hat JBOSS Data Grid
Article

Enabling LDAP Security for DataGrid Cache

Kamesh Sampath

Expanding on Tristan's blog, where he spoke of enabling security for JBoss Data Grid caches, in this post we will cover how to add LDAP based security to the JDG caches. The principles and techniques remain defined by Tristan, but there are some minor changes that I will be highlighting in this blog for a successful working configuration of JDG enabled with LDAP security. Before we jump on to configuring the JDG for security, I would like to brush up...

Red Hat JBOSS Data Grid
Article

Offload your database data into an in-memory data grid for fast processing made easy

Cojan van Ballegooijen

An in-memory data grid is a distributed data management platform for application data that: Uses memory (RAM) to store information for very fast, low-latency response time, and very high throughput. Keeps copies of that information synchronized across multiple servers for continuous availability, information reliability, and linear scalability. Can be used as distributed cache, NoSQL database, event broker, compute grid, and Apache Spark data store. The technical advantages of an in-memory data grid (IMDGs) provide business benefits in the form of...

Article Thumbnail
Article

External materialized views demystified in Red Hat JBoss Data Virtualization and Red Hat JBoss Data Grid

Cojan van Ballegooijen

Red Hat JBoss Data Virtualization (JDV) provides several capabilities for caching data including: materialized views, result set caching, and code table caching. These techniques can be used to significantly improve performance in many situations. With the exception of external materialized views, the cached data is accessed through the BufferManager. For better performance, the BufferManager setting should be adjusted to the memory constraints of your installation. See the Admin Guide for more on parameter tuning. JDV supports two kinds of caching...

Internet of things feature image
Article

Wearable Tech: A Developer’s Security Nightmare

Samantha Donaldson

Web developers and IT professionals are the foundations of any quality business’ data security. However, with technology constantly changing and evolving as well as becoming more consumer-friendly, this data’s vulnerability only increases and it can often be hard to even notice how this new technology can actually affect your company until it occurs. Despite this, ignorance to modern hacking techniques does not refute their inability to transform even the smallest of devices into a weapon with which to infect or...

JBoss Data Virtualization: Integrating with Impala on Cloudera
Article

Unlock your Red Hat JBoss Data Grid data with Red Hat JBoss Data Virtualization

Cojan van Ballegooijen

Welcome to another episode of the series: “Unlock your Red Hat JBoss Data Grid (JDG) data with Red Hat JBoss Data Virtualization (JDV).” This post will guide you through an example of connecting to Red Hat JBoss Data Grid data source, using Teiid Designer. In this example, we will demonstrate connecting to a local JDG data source. We’re using the JDG 6.6.1, but you can connect to any local or remote JDG source (version 6.6.1) if you wish, using the...

Red Hat OpenShift
Article

Running Spark Jobs On OpenShift

Zak Hassan

Introduction: A feature of OpenShift is jobs and today I will be explaining how you can use jobs to run your spark machine, learning data science applications against Spark running on OpenShift. You can run jobs as a batch or scheduled, which provides cron like functionality. If jobs fail, by default OpenShift will retry the job creation again. At the end of this article, I have a video demonstration of running spark jobs from OpenShift templates against Spark running on...

WildFly Swarm Logo
Article

Putting the “Micro” in Microservices with WildFly Swarm

Chris Tozzi

Do you like JavaEE apps, but wonder how to fit them into a microservices-centric workflow? WildFly Swarm is the answer. I know—“Java” and “microservices” are not words that seem to go together. Java is an old, relatively unsexy programming language. It’s a pretty useful one, but it was created long before the era of Continuous Delivery, containers and microservices. But that doesn’t mean you have to give up on Java if you want to take advantage of microservices. WildFly Swarm...

Article Thumbnail
Article

Announcing Red Hat JBoss Data Grid 7

Cojan van Ballegooijen

We are very excited to announce General Availability (GA) of Red Hat JBoss Data Grid (JDG) 7! JDG supercharges today’s modern applications and allows developers to meet tough requirements of high performance, availability, reliability, and elastic scale. JBoss Data Grid is compatible with the existing data tier as well as applications written in any language, using any framework and any platform via multiple APIs such as memcached, HotRod, and REST. Red Hat JBoss Data Grid empowers developers to obtain a...

Node JS logo
Article

DevNation Live Blog: Building Reactive Applications with Node.js and Red Hat JBoss Data Grid

Rob Terzi

At DevNation, Red Hat's Galder Zamarreño gave a talk with a live demo, Building reactive applications with Node.js and Red Hat JBoss Data Grid. The demo consisted of building an event-based three tier web application using JBoss Data Grid (JDG) as the data layer, an event manager running on Node.js, and a web client. Recently, support for Node.js clients was added to JDG, opening up the performance of a horizontally scalable in-memory data grid, to reactive web and mobile applications...